Probabilistic stability analysis of earth dam slope under transient seepage using multivariate adaptive regression splines

Wang, Lin; Wu, Chongzhi; Gu, Xiaoqiang; Liu, Hanlong; Mei, Guoxiong; Zhang, Wengang

doi:10.1007/s10064-020-01730-0

Cited by 176 publications

(36 citation statements)

References 48 publications

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“…technique until the 'lack of fit' criterion is a minimum and forecasting accuracy enhancement (Wang et al 2020). The GCV value is given as follows (Mohanta &Patra 2019, Zheng et al…”

Section: Multivariate Adaptive Regression Spline (Mars)mentioning

confidence: 99%

WITHDRAWN: Forecasting Daily Global Solar Radiation in Hot Semi-Arid Climate Using a Novel Hybrid Machine Learning Paradigm

Jamei¹,

Ahmadianfar²,

Jamei³

et al. 2021

Preprint

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Solar energy is one of the most important renewable energy sources. Assessing the solar potential of area needs analyzed information about the dataset of the measured global solar radiation (GSR). Recently, researches detected the high potential of state-of-the-art artificial intelligence (AI) methods in estimating the GSR successfully. In this study, a novel hybrid AI-based tool consisting of least square support vector machine (LSSVM) integrated with improved simulated annealing (ISA) is proposed to predict the GSR over the Ahvaz synoptic station located in the South-West of Iran. The potential of the proposed hybrid paradigm so-called LSSVM-ISA was evaluated by using multivariate adaptive regression spline (MARS), generalization regression neural network (GRNN), and multivariate linear regression with interactions (MLRI). For precise assessment of efficiency of the AI models, various statistical metrics and validation methods were used to assess the precision of the developed models. A comparison of the obtained results indicated that the LSSVM-ISA method performed better than the MARS, GRNN, and MLRI models. The achieved RMSE values of the MARS, GRNN, and MLRI models were decreased by 9%, 16%, and 30% using the LSSVM-ISA model. Finally, the results demonstrated that the LSSVM-ISA model could be successfully employed for accurately predicting GSR.

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“…technique until the 'lack of fit' criterion is a minimum and forecasting accuracy enhancement (Wang et al 2020). The GCV value is given as follows (Mohanta &Patra 2019, Zheng et al…”

Section: Multivariate Adaptive Regression Spline (Mars)mentioning

confidence: 99%

WITHDRAWN: Forecasting Daily Global Solar Radiation in Hot Semi-Arid Climate Using a Novel Hybrid Machine Learning Paradigm

Jamei¹,

Ahmadianfar²,

Jamei³

et al. 2021

Preprint

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show abstract

“…A large number of applications in civil engineering relate to groundwater flow, such as slope stability [21][22][23]; surface/subsurface soil erosion and sediment transport [24][25][26]; dam safety, including piping under and through dams [27][28][29][30][31][32]; groundwater contamination [33][34][35][36]; stability of artificially freezing ground [37,38]; sustainable management of water resources [39][40][41][42]; interaction between groundwater and surface water [43,44]; and karst collapse pillars [45][46][47].…”

Section: Introductionmentioning

confidence: 99%

Seepage Velocity: Large Scale Mapping and the Evaluation of Two Different Aquifer Conditions (Silty Clayey and Sandy)

et al. 2020

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Seepage velocity is a very important criterion in infrastructure construction. The planning of numerous large infrastructure projects requires the mapping of seepage velocity at a large scale. To date, however, no reliable approach exists to determine seepage velocity at such a scale. This paper presents a tool within ArcMap/Geographic Information System (GIS) software that can be used to map the seepage velocity at a large scale. The resultant maps include both direction and magnitude mapping of the seepage velocity. To verify the GIS tool, this study considered two types of aquifer conditions in two regions in Iraq: silty clayey (Babylon province) and sandy (Dibdibba in Karbala province). The results indicate that, for Babylon province, the groundwater flows from the northwest to southeast with a seepage velocity no more than 0.19 m/d; for the Dibdibba region, the groundwater flows from the west to the east with a seepage velocity not exceeding 0.27 m/d. The effectiveness of the presented tool in depicting the seepage velocity was thus demonstrated. The accuracy of the resultant maps depends on the resolution of the four essential maps (groundwater elevation head, effective porosity, saturated thickness, and transmissivity) and locations of wells that are used to collect the data.

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“…For each cluster, the sum of squares is calculated, and the two clusters with the smallest increase in the overall sum of squares within cluster distances are combined. Ward's method and the average linkage method have been shown to perform better than the other procedures [35,39].…”

Section: Hierarchical Clustering and R-mode Analysismentioning

confidence: 99%

Classification of rock types using multivariate analysis in the Dezak area, SW Iran

et al. 2020

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The geochemical multivariate techniques were applied to recognize different geological units and categorized rock types which accompanied by different penalties. Knowing changes and classification of raw materials with macroscopic and microscopic quantification have direct effect on economic and efficiency in a precipitated calcium carbonate plant. Based on lithological changes, the Darian Formation was divided into four rock units based on a total of 492 chip samples collected from the study area. The main aim objective of this study was to classify the rock types in this area using a multivariate analysis combining the R-mode factor analysis and K-Means method. Due to the opposite vector orientation of SiO

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Probabilistic stability analysis of earth dam slope under transient seepage using multivariate adaptive regression splines

Cited by 176 publications

References 48 publications

WITHDRAWN: Forecasting Daily Global Solar Radiation in Hot Semi-Arid Climate Using a Novel Hybrid Machine Learning Paradigm

WITHDRAWN: Forecasting Daily Global Solar Radiation in Hot Semi-Arid Climate Using a Novel Hybrid Machine Learning Paradigm

Seepage Velocity: Large Scale Mapping and the Evaluation of Two Different Aquifer Conditions (Silty Clayey and Sandy)

Classification of rock types using multivariate analysis in the Dezak area, SW Iran

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